DeBERTa v3 (small) fine-tuned on SST2
This model is a fine-tuned version of microsoft/deberta-v3-small on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2134
- Accuracy: 0.9404
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.176 | 1.0 | 4210 | 0.2134 | 0.9404 |
0.1254 | 2.0 | 8420 | 0.2362 | 0.9415 |
0.0957 | 3.0 | 12630 | 0.3187 | 0.9335 |
0.0673 | 4.0 | 16840 | 0.3039 | 0.9266 |
0.0457 | 5.0 | 21050 | 0.3521 | 0.9312 |
Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3
- Downloads last month
- 18
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for mrm8488/deberta-v3-small-finetuned-sst2
Dataset used to train mrm8488/deberta-v3-small-finetuned-sst2
Evaluation results
- Accuracy on GLUE SST2self-reported0.940
- Accuracy on gluevalidation set verified0.940
- Precision on gluevalidation set verified0.938
- Recall on gluevalidation set verified0.946
- AUC on gluevalidation set verified0.980
- F1 on gluevalidation set verified0.942
- loss on gluevalidation set verified0.213